#nvidia

#nvidia

OpenAI's growing compute needs have led it to form new partnerships beyond Microsoft, including with Google, signaling unexpectedly strong infrastructure demand.

Hamzaogullari isn't alone. This week, Loop Capital analyst Ananda Baruah raised Nvidia's price target to $250 from $175, a level that would equate to a roughly $6 trillion market value.

Nvidia holds over 80% of the AI accelerator market with its H100/H200 GPUs, positioning it strategically to capitalize on the $400 billion AI chip market by 2030.

DeepSeek has reportedly stalled in the development of its future R2 model because the company does not have access to sufficient GPUs from Nvidia, according to a report.

The RTX 5050 GPU, set for a mid-July release, is already being integrated into laptops by various OEMs, with early listings coming from Chinese manufacturers.

Investors seeking higher yields than the paltry 0.03% from NVIDIA stock may consider the NVDY ETF, which offers a massive, albeit risky, distribution yield.

Asus has updated its ROG G16 and TUF Gaming F16 laptops with the latest Intel processors and Nvidia's RTX 5050 GPU, catering to gamers and performance enthusiasts.

AI models are energy-hungry and will drive increased cloud computing consumption. Data centers worldwide consumed roughly 1.5% of global electricity, and that number is expected to grow.

Market sentiment has turned fearful now that tensions between Israel and Iran have worsened, leading to a notable drop in technology stocks and impacting major indices.

Nvidia aims to create the world's first industrial AI cloud with Deutsche Telekom to support AI-driven manufacturing and promote AI adoption across industries.

JFrog and NVIDIA have expanded integrations to include the Enterprise AI Factory, enabling the management of AI applications through JFrog's Software Supply Chain Platform.

Serverless GPU acceleration represents a major advancement in making cutting-edge AI computing more accessible. With seamless access to NVIDIA L4 GPUs, developers can now bring AI applications to production faster and more cost-effectively than ever before.